Neighbor-Aware Distributed Task Offloading Algorithm in Energy-Harvesting Internet of Things

被引:2
|
作者
Lee, Jaewook [1 ]
Ko, Haneul [2 ]
机构
[1] Elect & Telecommun Res Inst, Network Res Div, Daejeon 34129, South Korea
[2] Kyung Hee Univ, Dept Elect Engn, Yongin 17104, Gyeonggi, South Korea
来源
IEEE INTERNET OF THINGS JOURNAL | 2023年 / 10卷 / 10期
关键词
Task analysis; Internet of Things; Cloud computing; Energy harvesting; Optimization; Mobile handsets; Heuristic algorithms; Distributed task offloading; edge cloud; edge computing; energy harvesting; stochastic game; EDGE; OPTIMIZATION; MANAGEMENT; FRAMEWORK; NETWORKS;
D O I
10.1109/JIOT.2022.3232710
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In the distributed task offloading system, the desired task completion time cannot be achieved when lots of mobile devices offload simultaneously the tasks with high complexity to a specific edge cloud. In this research, we present a neighbor-aware distributed task offloading algorithm (NA-DTOA) where the IoT device takes its energy status and the decisions of neighbor devices into account for the decisions on whether to process the task by itself and on which edge cloud is selected to offload the task. To decrease the task completion time while maintaining the average energy outage probability below the specified threshold, we design a constrained stochastic game model. To achieve the solution of the model, a best response dynamics-based algorithm is devised. The evaluation results reveal that, compared to a probability-based scheme, NA-DTOA reduces the average task completion time by almost 47% while ensuring a substantially low-average energy outage probability of 0.03.
引用
收藏
页码:8744 / 8753
页数:10
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